In order for content to be useful to users it first needs to be discovered. Search engines are known to determine relevance and provide content based on relevance. However, search engines are typically designed to analyze arbitrary content, and their algorithms are generally robust so as to adequately deal with the unknown or, worse, malicious or search-engine optimized content. Determination of relevance often suffers as a result, particularly within a narrowly defined field of content, such as financial information.
In addition, search engines fail to adequately identify or quantify user interactions with content. This may be a result of the need for robustness. Interactions with public content by the general public can be quite different from interactions by professionals with content related to their field.
Furthermore, search engine-determined relevance fails to adequately take into account other modes of content delivery. Parallel channels of distribution are often overlooked or poorly quantized.